This role is for one of the Weekday's clients

Salary range: Rs 4000000 - Rs 6500000 (ie INR 40-65 LPA)

Min Experience: 5 years

Location: Bengaluru

JobType: full-time

We are seeking a Lead AI Engineer to drive the development and deployment of cutting-edge LLMs (Large Language Models) and agent-based AI systems. This role involves working across the entire AI lifecycle—from identifying use cases to deploying and optimizing models in production. We’re looking for an experienced technical leader who can independently innovate and deliver impactful AI solutions.

Requirements

Key Responsibilities

• LLM & NLP Model Development – Design, fine-tune, and deploy large language models (GPT-3/4, T5, BERT, etc.) for tasks such as text generation, summarization, sentiment analysis, and information retrieval.
• Agentic System Design – Build and deploy autonomous, goal-driven AI agents that can interact with complex environments to accomplish specific objectives.
• End-to-End Project Ownership – Lead AI initiatives from ideation to production, managing the full model lifecycle independently.
• Cross-Functional Collaboration – Work closely with product, engineering, and operations teams to transform business requirements into AI-driven solutions, particularly in LLMs and agentic AI.
• Model Optimization & Evaluation – Enhance models for scalability, accuracy, and efficiency, continuously monitoring and fine-tuning performance in production.
• Research & Experimentation – Stay updated with the latest advancements in prompt engineering, reinforcement learning, and agent-based AI, assessing their real-world applicability.
• Documentation & Knowledge Sharing – Maintain detailed documentation of architectures, model performance, and insights while sharing best practices across the organization.

Requirements

• 5+ years of experience in AI and machine learning, with a strong focus on LLMs and agentic system development.
• Expertise in NLP & LLMs – Hands-on experience with large language models (GPT-3/4, Claude, etc.), transformer architectures, fine-tuning, and prompt engineering.
• Agentic AI Development – Proficiency in building and deploying autonomous AI agents using reinforcement learning (RL) or other goal-oriented frameworks.
• Strong Technical Skills – Advanced proficiency in Python and ML frameworks like Hugging Face Transformers, TensorFlow, PyTorch, along with data processing using Pandas and NumPy.
• MLOps & Deployment – Experience deploying large-scale AI models and agentic systems using Docker, Kubernetes, MLFlow, or similar MLOps frameworks.
• Data Management Expertise – Familiarity with data engineering principles, handling large datasets, real-time data processing, and cloud platforms (AWS, GCP, Azure).
• Independent Problem Solving – Strong analytical and problem-solving skills, with a proven ability to tackle complex AI challenges autonomously.
• Effective Communication – Ability to articulate technical concepts clearly to non-technical stakeholders and document solutions effectively.

Nice-to-Have

• Advanced Degree – Master’s or Ph.D. in AI, Machine Learning, Computer Science, or a related field.
• Finance AI Expertise – Experience applying AI in financial services, with an understanding of compliance, privacy, and domain-specific challenges.
• Reinforcement Learning Knowledge – Familiarity with RL techniques for developing autonomous, adaptive AI agents.